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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Wind Performance Based Design for High-Rise Buildings

Mohammadi, Alireza 09 November 2016 (has links)
The rapid growth of high-rise high-density urban areas in coastal and near coastal, hurricane-prone cities has been observed globally and in the United States in recent decades. Favored by modern urban growth and planning policies, this trend is expected to accelerate in future. Recent climate change studies suggest a significant increase in the destructiveness of hurricanes in past 30 years by both increases in lifetime and intensity of hurricanes. Current prescriptive wind design approach does not provide transparent methods and criteria to reliably quantify the performance of buildings as well as the functional requirements necessary to accommodate large populations during extreme wind. Since this approach primarily intends to keep the structural system essentially elastic, the more efficient design may be achievable by allowing controlled inelasticity in structural components. All these facts put a great emphasis on using a reliable wind design and assessment approach evidently describing the performance of high-rise building to wind loads beyond the current design wind loads. This dissertation presents the development of a wind performance-based engineering approach and its practical implementation for three, 47-, 40- and 30-story steel moment frame high-rise buildings. In this study, the nonlinear dynamic responses of the buildings to different wind hazard levels were evaluated by developing 3D nonlinear finite element models and utilizing a wind incremental dynamic analysis (IDA) approach. The wind loading for the 47-story building was measured by conducting wind pressure testing on a scaled rigid model at the Wall of Wind (WOW) facility at Florida International University. For two other buildings wind loads were acquired using TPU Aerodynamic Database. Using the IDA results and adopting available wind performance criteria, a wind performance assessment approach was developed representing the estimated performance levels as a function of the basic wind speed. Three types of wind performance were evaluated: structural component performance; cladding performance to wind-induced shear deformation; and serviceability motion comfort performance. This evaluation indicated remarkable lateral capacity associated with allowing controlled structural nonlinearity, in contrast to considerations required to assure acceptable serviceability and non-structural (e.g. cladding) performances.
2

Statistical analysis of winddata regarding long-term correction / Statistisk analys av vinddata med avseendepå långtidskorrigering

Jonsson, Christoffer January 2010 (has links)
<p>The procedure of determining if a site is suitable for wind power production requiresconvincing statistical data describing the long-term behavior of the average wind speed.This can be achieved by measuring the wind speed for a short time period, e.g. a year,and after that a Measure-Correlate-Predict (MCP) method can be performed. The shorttermmeasured wind data must be used in combination with a long-term referenceseries. This long-term reference series can be global reanalysis data reaching 20 to 30years back in time. In a MCP method different regression methods can be used. Aftercreating a long-term corrected wind data series, it is possible to analyze the conditionsat the investigated site. To be able to study the behavior of different reference series andregression methods, a model was created in MATLAB. As short-term wind speed dataVattenfall Wind Power supplied data from two measuring masts, Ringhals andOskarshamn, with maximum heights of 96 and 100 meters, respectively. From UppsalaUniversity data were supplied from a measuring mast near Marsta with maximummeasurement height of 29 meters.When creating these long-term corrected wind data series there were many methodsavailable. In this Master thesis methods such as Ordinary-Least-Square, Least-Absolute-Deviation and Reduced-Major-Axis regression methods have been used. With eachmethod three reference series were used in combination with the short-termmeasurement data. These were data from NCAR 850 hPa, NCAR 42-meter sigma leveland a confidential source.Regression methods in combination with reference series were studied and the deviationfrom mean wind speed was obtained for each of these cases. Studies were performed onhow the length of the short-term measurement series affected the deviation from themeasured mean wind speed. It was also investigated if the time of the year had anyinfluence on the measurements.The general conclusion drawn after performing the above-mentioned studies was thatthe NCAR 850 hPa wind speed data and the Reduced-Major-Axis regression methodgave the smallest deviation from the measured mean wind speed in most cases. It wasalso concluded that when a short-term measurement series reached 10 to 14 monthsthere was a significant decrease in deviation from the mean wind speed, regardless ofreference series or method used. Calculations from the model regarding seasonaldependence stated that there was a slight dependency on which period of the year ameasurement was performed.</p> / <p>I processen att bedöma om en plats är lämplig för utbyggnad av vindkraft måste detfinnas övertygande statistiska data som beskriver den genomsnittliga vindhastighetenöver en längre tid. Genom att utföra vindhastighetsmätningar på den tänkta platsenunder en kortare tid, exempelvis ett år, och därefter tillämpas en Measure-Correlate-Predict (MCP) metod i kombination med en långtidsreferens, exempelvis en globalmodell som sträcker sig 20 till 30 år bakåt i tiden kan detta göras. I en MCP-metod kanolika typer av regressionsmetoder användas. När en långtidskorrigerad vinddataseriefinns tillgänglig kan dess beteende på den tänkta platsen analyseras. För att kunna göradetta för flera olika typer av referensserier och regressionsmetoder skapades en modell iMATLAB. Två vinddataserier erhölls från Vattenfall Vindkraft. Dessa var Ringhals ochOskarshamn med högsta mäthöjd på 96 respektive 100 meter. En ytterligarevinddataserie erhölls av Uppsala Universitet från en mätmast nära Marsta med högstamäthöjd på 29 meter.Det fanns flera metoder tillgängliga för att skapa de långtidskorrigeradevinddataserierna. I det här examensarbetet har metoderna Ordinary-Least-Square-,Least-Absolute-Deviation- och Reduced-Major-Axis regressioner använts. För varjemetod testades tre referensserier i kombination med de kortare vinddataserierna. Dessavar NCAR 850 hPa vindhastigheter, NCAR 42 meters sigmanivå vindhastigheter ochannan meteorologisk data.Regressionsmetoderna utvärderades genom att avvikelsen från de kortare mätseriernasmedelvindhastigheter beräknades. Det undersöktes också hur längden på användvinddata från de kortare mätserierna påverkade avvikelsen i medelvindhastighet och omdet fanns något säsongsberoende på när under året som mätningen av vinddata vargjord.Slutsatserna från undersökningarna var att NCAR 850 hPa vindhastigheter ochregressionsmetoden Reduced-Major-Axis generellt gav de lägsta avvikelserna frånuppmätt medelvindhastighet. Slutsatser kunde också dras om längden av användmätdata. Det var tydligt att oavsett referensserie och regressionsmetod uppstod enminskningen i avvikelse från medelvindhastigheten mellan 10 till 14 månaders längd påmätserien. Resultat angående säsongsberoende kunde påvisas i form av avvikelsermellan mätningar gjorda under olika tidpunkter på året. Storlek och tecken påavvikelsen berodde på vilken referensserien i kombination med regressionsmetod somanvändes.</p>
3

Statistical analysis of wind data regarding long-term correction / Statistisk analys av vinddata med avseendepå långtidskorrigering

Jonsson, Christoffer January 2010 (has links)
The procedure of determining if a site is suitable for wind power production requiresconvincing statistical data describing the long-term behavior of the average wind speed.This can be achieved by measuring the wind speed for a short time period, e.g. a year,and after that a Measure-Correlate-Predict (MCP) method can be performed. The shorttermmeasured wind data must be used in combination with a long-term referenceseries. This long-term reference series can be global reanalysis data reaching 20 to 30years back in time. In a MCP method different regression methods can be used. Aftercreating a long-term corrected wind data series, it is possible to analyze the conditionsat the investigated site. To be able to study the behavior of different reference series andregression methods, a model was created in MATLAB. As short-term wind speed dataVattenfall Wind Power supplied data from two measuring masts, Ringhals andOskarshamn, with maximum heights of 96 and 100 meters, respectively. From UppsalaUniversity data were supplied from a measuring mast near Marsta with maximummeasurement height of 29 meters.When creating these long-term corrected wind data series there were many methodsavailable. In this Master thesis methods such as Ordinary-Least-Square, Least-Absolute-Deviation and Reduced-Major-Axis regression methods have been used. With eachmethod three reference series were used in combination with the short-termmeasurement data. These were data from NCAR 850 hPa, NCAR 42-meter sigma leveland a confidential source.Regression methods in combination with reference series were studied and the deviationfrom mean wind speed was obtained for each of these cases. Studies were performed onhow the length of the short-term measurement series affected the deviation from themeasured mean wind speed. It was also investigated if the time of the year had anyinfluence on the measurements.The general conclusion drawn after performing the above-mentioned studies was thatthe NCAR 850 hPa wind speed data and the Reduced-Major-Axis regression methodgave the smallest deviation from the measured mean wind speed in most cases. It wasalso concluded that when a short-term measurement series reached 10 to 14 monthsthere was a significant decrease in deviation from the mean wind speed, regardless ofreference series or method used. Calculations from the model regarding seasonaldependence stated that there was a slight dependency on which period of the year ameasurement was performed. / I processen att bedöma om en plats är lämplig för utbyggnad av vindkraft måste detfinnas övertygande statistiska data som beskriver den genomsnittliga vindhastighetenöver en längre tid. Genom att utföra vindhastighetsmätningar på den tänkta platsenunder en kortare tid, exempelvis ett år, och därefter tillämpas en Measure-Correlate-Predict (MCP) metod i kombination med en långtidsreferens, exempelvis en globalmodell som sträcker sig 20 till 30 år bakåt i tiden kan detta göras. I en MCP-metod kanolika typer av regressionsmetoder användas. När en långtidskorrigerad vinddataseriefinns tillgänglig kan dess beteende på den tänkta platsen analyseras. För att kunna göradetta för flera olika typer av referensserier och regressionsmetoder skapades en modell iMATLAB. Två vinddataserier erhölls från Vattenfall Vindkraft. Dessa var Ringhals ochOskarshamn med högsta mäthöjd på 96 respektive 100 meter. En ytterligarevinddataserie erhölls av Uppsala Universitet från en mätmast nära Marsta med högstamäthöjd på 29 meter.Det fanns flera metoder tillgängliga för att skapa de långtidskorrigeradevinddataserierna. I det här examensarbetet har metoderna Ordinary-Least-Square-,Least-Absolute-Deviation- och Reduced-Major-Axis regressioner använts. För varjemetod testades tre referensserier i kombination med de kortare vinddataserierna. Dessavar NCAR 850 hPa vindhastigheter, NCAR 42 meters sigmanivå vindhastigheter ochannan meteorologisk data.Regressionsmetoderna utvärderades genom att avvikelsen från de kortare mätseriernasmedelvindhastigheter beräknades. Det undersöktes också hur längden på användvinddata från de kortare mätserierna påverkade avvikelsen i medelvindhastighet och omdet fanns något säsongsberoende på när under året som mätningen av vinddata vargjord.Slutsatserna från undersökningarna var att NCAR 850 hPa vindhastigheter ochregressionsmetoden Reduced-Major-Axis generellt gav de lägsta avvikelserna frånuppmätt medelvindhastighet. Slutsatser kunde också dras om längden av användmätdata. Det var tydligt att oavsett referensserie och regressionsmetod uppstod enminskningen i avvikelse från medelvindhastigheten mellan 10 till 14 månaders längd påmätserien. Resultat angående säsongsberoende kunde påvisas i form av avvikelsermellan mätningar gjorda under olika tidpunkter på året. Storlek och tecken påavvikelsen berodde på vilken referensserien i kombination med regressionsmetod somanvändes.

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